Noncoastal NMDS- With Ref Piedmont Streams
R version 4.0.3 (2020-10-10) – “Bunny-Wunnies Freak Out”
Packages used for NMDS: vegan (version 2.5-7)
Methods
The document shows a series of NMDS ordinations for reference benthic communities in Virginia with environmental characteristics overlaid to evaluate natural differences in community compositions across Virginia. These NMDS will support the Genus level IBI development process. This analysis is the first run of all of reference sites, reference West Virginia DEP sites, and sites that were deemed reference piedmont sites in Virginia. Reference sites were evaluated by regional biologists.
The dataset used includes all reference stations collected in Virginia that were deemed reference through a series or water quality parameter filters and regional biologist review. If stations appeared in the dataset more than 4 times, then the most recent 4 samples were used and the rest removed. Samples that had a total number of taxa below 100 collected at the time of sampling were also removed. Taxa that occurred in the dataset <= 5% of the time were removed. The data was log10 +1 transformed. Environmental factors were compiled for each station and used to plot over the NMDS to show environmental variation associated with the community matrix. The envfit function in Vegan was used to plot the continuous environmental variables. Some environmental variables like precipitation, slope, and elevation have not been calculated for all watersheds yet and will be added at a later date.
The first step was to read in the reference site bug taxa list and environmental factors dataset for each station. Join the environmental dataset with the bug dataset to account for multiple observations of each station and collection date and time.
Check to make sure the bug and environmental join was successful:
Number of rows in Community Matrix: 885
Number or rows in Environmental Matrix: 886
The data was log10+1 transformed. Rare taxa (<=5%) were removed.
NMDS Results for Non-Coastal Streams
## Run 0 stress 0.1736192
## Run 1 stress 0.173711
## ... Procrustes: rmse 0.003228835 max resid 0.04416222
## Run 2 stress 0.1767676
## Run 3 stress 0.1748688
## Run 4 stress 0.1741778
## Run 5 stress 0.1741189
## ... Procrustes: rmse 0.004195746 max resid 0.05510594
## Run 6 stress 0.1737059
## ... Procrustes: rmse 0.002513765 max resid 0.05072623
## Run 7 stress 0.1744884
## Run 8 stress 0.1735867
## ... New best solution
## ... Procrustes: rmse 0.001833516 max resid 0.04382191
## Run 9 stress 0.1743853
## Run 10 stress 0.1739469
## ... Procrustes: rmse 0.002267956 max resid 0.05032217
## Run 11 stress 0.1739365
## ... Procrustes: rmse 0.004646453 max resid 0.0525155
## Run 12 stress 0.1740398
## ... Procrustes: rmse 0.00366061 max resid 0.05422801
## Run 13 stress 0.1742292
## Run 14 stress 0.1741323
## Run 15 stress 0.1736095
## ... Procrustes: rmse 0.002330499 max resid 0.04743859
## Run 16 stress 0.1736815
## ... Procrustes: rmse 0.003054224 max resid 0.05109447
## Run 17 stress 0.1737134
## ... Procrustes: rmse 0.002979084 max resid 0.05099102
## Run 18 stress 0.1744563
## Run 19 stress 0.1742569
## Run 20 stress 0.1736935
## ... Procrustes: rmse 0.003004436 max resid 0.0514255
## Run 21 stress 0.1736302
## ... Procrustes: rmse 0.002359916 max resid 0.04350769
## Run 22 stress 0.1745518
## Run 23 stress 0.1744939
## Run 24 stress 0.1739928
## ... Procrustes: rmse 0.003724485 max resid 0.09843851
## Run 25 stress 0.17649
## Run 26 stress 0.1763165
## Run 27 stress 0.1763304
## Run 28 stress 0.1741695
## Run 29 stress 0.1762735
## Run 30 stress 0.1736982
## ... Procrustes: rmse 0.00360717 max resid 0.05158585
## Run 31 stress 0.1745924
## Run 32 stress 0.1741441
## Run 33 stress 0.176818
## Run 34 stress 0.17892
## Run 35 stress 0.1747579
## Run 36 stress 0.1744434
## Run 37 stress 0.1777086
## Run 38 stress 0.1740838
## ... Procrustes: rmse 0.00292258 max resid 0.05097342
## Run 39 stress 0.1763889
## Run 40 stress 0.1765311
## Run 41 stress 0.1777524
## Run 42 stress 0.1736737
## ... Procrustes: rmse 0.003569905 max resid 0.05152866
## Run 43 stress 0.1744102
## Run 44 stress 0.1774187
## Run 45 stress 0.174176
## Run 46 stress 0.177629
## Run 47 stress 0.1745761
## Run 48 stress 0.1735585
## ... New best solution
## ... Procrustes: rmse 0.001530324 max resid 0.03535403
## Run 49 stress 0.1768286
## Run 50 stress 0.179401
## Run 51 stress 0.173847
## ... Procrustes: rmse 0.005148901 max resid 0.05260652
## Run 52 stress 0.1739136
## ... Procrustes: rmse 0.002367953 max resid 0.05158899
## Run 53 stress 0.1740037
## ... Procrustes: rmse 0.001774381 max resid 0.05122278
## Run 54 stress 0.1793386
## Run 55 stress 0.1740558
## ... Procrustes: rmse 0.002350821 max resid 0.05079955
## Run 56 stress 0.1782129
## Run 57 stress 0.1747037
## Run 58 stress 0.1744895
## Run 59 stress 0.1741021
## Run 60 stress 0.1741039
## Run 61 stress 0.1745953
## Run 62 stress 0.1739453
## ... Procrustes: rmse 0.00288339 max resid 0.04959315
## Run 63 stress 0.1770524
## Run 64 stress 0.1738314
## ... Procrustes: rmse 0.004992195 max resid 0.05256934
## Run 65 stress 0.17491
## Run 66 stress 0.1743824
## Run 67 stress 0.1740452
## ... Procrustes: rmse 0.004606132 max resid 0.09085112
## Run 68 stress 0.1736759
## ... Procrustes: rmse 0.002933027 max resid 0.05088994
## Run 69 stress 0.1752478
## Run 70 stress 0.1737831
## ... Procrustes: rmse 0.002628352 max resid 0.04822576
## Run 71 stress 0.1746318
## Run 72 stress 0.1735876
## ... Procrustes: rmse 0.002003344 max resid 0.03926261
## Run 73 stress 0.1757354
## Run 74 stress 0.1740912
## Run 75 stress 0.1741092
## Run 76 stress 0.1741614
## Run 77 stress 0.173949
## ... Procrustes: rmse 0.002876984 max resid 0.05097641
## Run 78 stress 0.1744866
## Run 79 stress 0.1740386
## ... Procrustes: rmse 0.004665476 max resid 0.05475222
## Run 80 stress 0.1737691
## ... Procrustes: rmse 0.004455867 max resid 0.05220263
## Run 81 stress 0.1736806
## ... Procrustes: rmse 0.003266647 max resid 0.05122082
## Run 82 stress 0.1741808
## Run 83 stress 0.1740471
## ... Procrustes: rmse 0.004764423 max resid 0.05494471
## Run 84 stress 0.1736636
## ... Procrustes: rmse 0.004314095 max resid 0.05217346
## Run 85 stress 0.1736453
## ... Procrustes: rmse 0.003407475 max resid 0.05161344
## Run 86 stress 0.1744886
## Run 87 stress 0.1739551
## ... Procrustes: rmse 0.004850287 max resid 0.05258343
## Run 88 stress 0.1736488
## ... Procrustes: rmse 0.004233127 max resid 0.05212705
## Run 89 stress 0.1741455
## Run 90 stress 0.1735499
## ... New best solution
## ... Procrustes: rmse 0.001408344 max resid 0.03949764
## Run 91 stress 0.1736321
## ... Procrustes: rmse 0.002391714 max resid 0.04387407
## Run 92 stress 0.1736561
## ... Procrustes: rmse 0.00237832 max resid 0.05095219
## Run 93 stress 0.1804484
## Run 94 stress 0.1747737
## Run 95 stress 0.1787652
## Run 96 stress 0.1756345
## Run 97 stress 0.1749759
## Run 98 stress 0.1744952
## Run 99 stress 0.1793076
## Run 100 stress 0.1737234
## ... Procrustes: rmse 0.00258629 max resid 0.05103345
## Run 101 stress 0.1740363
## ... Procrustes: rmse 0.004670626 max resid 0.05469367
## Run 102 stress 0.1736296
## ... Procrustes: rmse 0.004424124 max resid 0.05212076
## Run 103 stress 0.1741639
## Run 104 stress 0.1738685
## ... Procrustes: rmse 0.004863736 max resid 0.05226244
## Run 105 stress 0.1739921
## ... Procrustes: rmse 0.005149799 max resid 0.05454243
## Run 106 stress 0.1736289
## ... Procrustes: rmse 0.004457153 max resid 0.05216681
## Run 107 stress 0.1793248
## Run 108 stress 0.1789845
## Run 109 stress 0.1741486
## Run 110 stress 0.1752618
## Run 111 stress 0.1736687
## ... Procrustes: rmse 0.003828466 max resid 0.05186973
## Run 112 stress 0.1744662
## Run 113 stress 0.1736059
## ... Procrustes: rmse 0.002177408 max resid 0.04375274
## Run 114 stress 0.1741079
## Run 115 stress 0.1744514
## Run 116 stress 0.1791688
## Run 117 stress 0.1741022
## Run 118 stress 0.174059
## Run 119 stress 0.174651
## Run 120 stress 0.1744475
## Run 121 stress 0.1736999
## ... Procrustes: rmse 0.0007863275 max resid 0.009284998
## ... Similar to previous best
## *** Solution reached##
## Call:
## metaMDS(comm = NoncoastalFive[, 6:107], k = 3, trymax = 1000)
##
## global Multidimensional Scaling using monoMDS
##
## Data: NoncoastalFive[, 6:107]
## Distance: bray
##
## Dimensions: 3
## Stress: 0.1735499
## Stress type 1, weak ties
## Two convergent solutions found after 121 tries
## Scaling: centring, PC rotation, halfchange scaling
## Species: expanded scores based on 'NoncoastalFive[, 6:107]'
## NMDS1 NMDS2 r2 Pr(>r)
## Year -0.99274 -0.12029 0.0160 0.19
## JulianDate 0.40449 -0.91454 0.7224 0.01 **
## Latitude 0.49119 0.87105 0.0234 0.08 .
## Longitude 0.57064 0.82120 0.0340 0.02 *
## totalArea_sqMile 0.78844 0.61512 0.3327 0.01 **
## ELEVMEAN -0.90407 -0.42738 0.2149 0.01 **
## SLPMEAN -0.87177 -0.48991 0.1569 0.01 **
## wshdRain_mmyr 0.77970 0.62615 0.3135 0.01 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 99Plot with Stations: Non-Coastal
Season: Non-Coastal
##
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$Season, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Fall Spring
## delta 0.6379 0.6358
## n 411 474
##
## Chance corrected within-group agreement A: 0.04938
## Based on observed delta 0.6368 and expected delta 0.6699
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999Reference Type: Re-Pied or Ref
##
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$JRH_Final_Ref_Cod, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Ref Ref-Pied WVA
## delta 0.6543 0.6468 0.5578
## n 685 99 101
##
## Chance corrected within-group agreement A: 0.04088
## Based on observed delta 0.6425 and expected delta 0.6699
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999Ecoregion: Non-Coastal
##
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$US_L3NAME, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Blue Ridge Central Appalachians Northern Piedmont Piedmont
## delta 0.5952 0.5932 0.6494 0.6306
## n 154 141 125 213
## Ridge and Valley
## delta 0.6568
## n 252
##
## Chance corrected within-group agreement A: 0.06158
## Based on observed delta 0.6286 and expected delta 0.6699
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999Basin: Non-Coastal
##
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$Basin_Code, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Appomattox Chowan-Dismal James-Middle James-Upper New
## delta 0.5578 0.5804 0.5794 0.6283 0.6536 0.65
## n 101 18 24 81 114 78
## Potomac-Lower Potomac-Shenandoah Rappahannock Roanoke Tennessee-Big Sandy
## delta 0.6482 0.6543 0.6404 0.6193 0.5996
## n 40 41 129 101 16
## Tennessee-Clinch Tennessee-Holston Yadkin York
## delta 0.6271 0.6244 0.5744 0.618
## n 50 53 4 35
##
## Chance corrected within-group agreement A: 0.0677
## Based on observed delta 0.6245 and expected delta 0.6699
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999Admin Region: Non-Coastal
##
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$ASSESS_REG, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## BRRO NRO PRO SWRO VRO
## delta 0.5578 0.6458 0.6637 0.6164 0.6323 0.6474
## n 101 258 198 55 156 117
##
## Chance corrected within-group agreement A: 0.05089
## Based on observed delta 0.6358 and expected delta 0.6699
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999##Bioregion: Non-Coastal
##
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$Bioregion, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Mountain Piedmont
## delta 0.6498 0.648
## n 547 338
##
## Chance corrected within-group agreement A: 0.03091
## Based on observed delta 0.6492 and expected delta 0.6699
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999Sample Method: Non-Coastal
##
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$Gradient, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## MACS Riffle
## delta 0.5578 0.6056 0.6582
## n 101 39 745
##
## Chance corrected within-group agreement A: 0.03792
## Based on observed delta 0.6445 and expected delta 0.6699
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999Stream Order: Non-Coastal
##
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$Order, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## 0 1 2 3 4 5
## delta NaN 0.6343 0.6605 0.6351 0.6125 0.5681
## n 1 341 231 175 104 33
##
## Chance corrected within-group agreement A: 0.0501
## Based on observed delta 0.6363 and expected delta 0.6699
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999Stream Order Categories: Non-coastal
##
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$StreamCate, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Large No order Small
## delta 0.6312 NaN 0.6541
## n 312 1 572
##
## Chance corrected within-group agreement A: 0.03561
## Based on observed delta 0.646 and expected delta 0.6699
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999Water Quality Standard Class: Non-Coastal
##
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$WQS_CLASS, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## III IV V VI
## delta 0.5578 0.6502 0.6436 0.6302 0.6018
## n 101 310 184 87 203
##
## Chance corrected within-group agreement A: 0.06669
## Based on observed delta 0.6252 and expected delta 0.6699
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999Natural Trout Water WQS: Non-Coastal
##
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$WQS_TROUT, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Yes
## delta 0.6771 0.6222
## n 595 290
##
## Chance corrected within-group agreement A: 0.01606
## Based on observed delta 0.6591 and expected delta 0.6699
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999#Ecoregion separated by Season
Bioregion and Season
##
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$BioregionSeason, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## MountainLargeFall MountainLargeSpring MountainNo orderFall
## delta 0.558 0.5802 NaN
## n 82 86 1
## MountainSmallFall MountainSmallSpring PiedmontLargeFall
## delta 0.6103 0.5738 0.5816
## n 156 222 74
## PiedmontLargeSpring PiedmontSmallFall PiedmontSmallSpring
## delta 0.5963 0.5977 0.6061
## n 70 98 96
##
## Chance corrected within-group agreement A: 0.1222
## Based on observed delta 0.588 and expected delta 0.6699
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999Bioregion, Stream Size and Season: Non-coastal
##
## Call:
## mrpp(dat = bugsnms_noncoast[, 6:107], grouping = samplescoresenv_noncoast$Bioregionsize, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## MountainLarge MountainNo order MountainSmall PiedmontLarge PiedmontSmall
## delta 0.605 NaN 0.6274 0.6195 0.6405
## n 168 1 378 144 194
##
## Chance corrected within-group agreement A: 0.06734
## Based on observed delta 0.6247 and expected delta 0.6699
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999#Bioregion separated by Season
